Trusted Routing Protocol for Flying Ad Hoc Networks

doi:10.3778/j.issn.1673-9418.2105073

Abstract

Abstract:

Aiming at the problems of being vulnerable to internal attacks and frequent link interruption in flying ad hoc networks (FANETs), a trust-based ad hoc on-demand multipath distance vector routing protocol (TAOMDV) is proposed. Firstly, a trust evaluation model is established. The packet forward ratio, trusted interaction and probe packet receive ratio are introduced as trust evaluation factors. An adaptive fuzzy trust aggregation network (AFTAN) is designed to calculate the direct trust of nodes, while the indirect trust of reliable neighbor nodes is integrated as well to calculate node trust. Secondly, the trust fluctuation penalty mechanism is introduced to resist the on-off attack in the trust model. Finally, the trust model is applied to ad hoc on-demand multipath distance vector (AOMDV) protocol. In the route discovery phase, the path trust is introduced as the basis for routing selection to establish a trusted path. In the route maintenance phase, the path alarm mechanism is applied to respond to malicious nodes in a timely manner. The simulation results show that the TAOMDV can not only defend against common attacks, such as black hole attack, gray hole attack and on-off attack, but also reduce the impact of topology changes and link interruptions. Compared with light-weight trust-enhanced ad hoc on-demand multipath distance vector (TEAOMDV), the proposed protocol effectively improves the delivery ratio and throughput of the network, which contributes to the better performance in routing overhead and average end-to-end delay.

Key words: flying ad hoc networks (FANETs), routing attack, trust model, trusted routing

摘要：

针对无人机自组织网络（FANETs）容易遭受内部攻击、链路中断频繁的问题，提出了一种基于信任的按需多径距离矢量路由协议（TAOMDV）。首先，建立了节点信任度评估模型，引入数据包转发率、可信交互度、探测包接收率作为信任评估因子，设计了自适应模糊信任聚合网络（AFTAN）计算节点的直接信任度，综合可信邻居节点的间接信任度以计算节点信任度。其次，引入信任波动惩罚机制，抵御信任模型中的开关攻击。最后，将信任模型应用于按需多径距离矢量路由协议（AOMDV）中，在路由发现阶段引入路径信任度作为路由选择依据，建立可信路径，在路由维护阶段通过路径报警机制对恶意节点做出及时响应。仿真结果表明TAOMDV不仅能抵御常见的黑洞、灰洞攻击与开关攻击，而且能够降低网络拓扑变更与链路中断的影响。与轻量级信任增强路由协议（TEAOMDV）相比，有效提高了网络的数据包投递率与吞吐量，优化了路由开销与平均端到端时延。

关键词: 无人机自组网（FANETs）, 路由攻击, 信任模型, 可信路由

ZHAO Beiying, JI Weifeng, WENG Jiang, SUN Yan, LI Yingqi, WU Xuan. Trusted Routing Protocol for Flying Ad Hoc Networks[J]. Journal of Frontiers of Computer Science and Technology, 2021, 15(12): 2304-2314.

赵蓓英, 姬伟峰, 翁江, 孙岩, 李映岐, 吴玄. 面向无人机自组网的可信路由协议[J]. 计算机科学与探索, 2021, 15(12): 2304-2314.

References

[1] YOU W J, DONG C, WU Q H. Survey of layered architecture in large-scale FANETs[J]. Computer Science, 2020, 47(9): 226-231.
游文静, 董超, 吴启晖. 大规模无人机自组网分层体系架构研究综述[J]. 计算机科学, 2020, 47(9): 226-231.
[2] CHRIKI A, TOUATI H, SNOUSSI H, et al. FANET: communication, mobility models and security issues[J]. Computer Networks, 2019, 163: 106877.
[3] KRISHNA C G L, MURPHY R R. A review on cybersecurity vulnerabilities for unmanned aerial vehicles[C]//Proceedings of the 2017 IEEE International Symposium on Safety, Security and Rescue Robotics, Shanghai, Oct 11-13, 2017. Piscataway: IEEE, 2017: 194-199.
[4] LI J, HUANG Y H, CUI G S, et al. Improvement of AOMDV protocol based on trust model[J]. Journal of Guilin University of Aerospace Technology, 2014, 19(1): 1-7.
李健, 黄延辉, 崔更申, 等. 基于信任模型的AOMDV协议的改进[J]. 桂林航天工业学院学报, 2014, 19(1): 1-7.
[5] XIA H, TIAN C L, PAN Z K, et al. Light-weight trust-enhanced on-demand multi-path routing in mobile ad hoc networks[J]. Journal of Network and Computer Applications, 2016, 62: 112-127.
[6] NIVEDITA V, NANDHAGOPAL N. Improving QoS and efficient multi-hop and relay based communication frame work against attacker in MANET[J]. Journal of Ambient Intelligence and Humanized Computing, 2020, 12(1): 4081-4091.
[7] SINGH K, VERMA A K. A fuzzy-based trust model for flying ad hoc networks (FANETs)[J]. International Journal of Communication Systems, 2018, 31: 23-47.
[8] SINGH K, VERMA A K. TBCS: a trust based clustering scheme for secure communication in flying ad-hoc networks[J]. Wireless Personal Communications, 2020, 114(4): 3173-3196.
[9] POUYAN A A, YADOLLAHZADEH TABARI M. FPN-SAODV: using fuzzy petri nets for securing AODV routing protocol in mobile ad hoc network[J]. International Journal of Communication Systems, 2017, 30(1): e2935.
[10] WEI Z, WANG F. On mitigating on-off attacks in wireless sensor networks[J]. IEICE Transactions on Fundamentals of Electronics Communications & Computer Sciences, 2018, 101(1): 298-301.
[11] TAO Y, PAN L N, WANG J, et al. A security trust evaluation model for wireless sensor networks defense against trust attacks[J]. Chinese Journal of Sensors and Actuators, 2018, 31(12): 1876-1881.
陶洋, 潘蕾娜, 王进, 等. 防御信任攻击的无线传感器网络安全信任评估模型[J]. 传感技术学报, 2018, 31(12): 1876-1881.
[12] XIE L X, WEI R X. Dynamic trust evaluation method for IoT nodes[J]. Journal of Computer Applications, 2019, 39(9): 2597-2603.
谢丽霞, 魏瑞炘. 物联网节点动态信任度评估方法[J]. 计算机应用, 2019, 39(9): 2597-2603.
[13] LIAO Q F, SUN D. Sparse and decoupling control strategies based on Takagi-Sugeno fuzzy models[J]. IEEE Transactions on Cybernetics, 2021, 51(2): 947-960.
[14] ZHANG B, SHIN Y C. A data-driven approach of Takagi-Sugeno fuzzy control of unknown nonlinear systems[J]. Applied Sciences, 2020, 11(1): 62-76.
[15] LIU X Y, ZHOU Z L. A novel prediction model based on particle swarm optimization and adaptive neuro-fuzzy inference system[J]. Journal of Intelligent & Fuzzy Systems, 2017, 33(1): 3137-3143.
[16] SINWAR D, SHARMA N, MAAKA S K, et al. Analysis and comparison of ant colony optimization algorithm with DSDV, AODV, and AOMDV based on shortest path in MANET[J]. Journal of Information and Optimization Sciences, 2020, 41(2): 621-632.